Documentation of 'ec.gp.breed.MutatePromotePipeline' Java class
MutatePromotePipeline
ec.gp.breed

Class MutatePromotePipeline

  • All Implemented Interfaces:
    Prototype, Setup, SteadyStateBSourceForm, RandomChoiceChooserD, java.io.Serializable, java.lang.Cloneable


    public class MutatePromotePipeline
    extends GPBreedingPipeline
    MutatePromotePipeline works very similarly to the PromoteNode algorithm described in Kumar Chellapilla, "A Preliminary Investigation into Evolving Modular Programs without Subtree Crossover", GP98, and is also similar to the "deletion" operator found in Una-May O'Reilly's thesis, "An Analysis of Genetic Programming".

    MutatePromotePipeline tries tries times to find a tree that has at least one promotable node. It then picks randomly from all the promotable nodes in the tree, and promotes one. If it cannot find a valid tree in tries times, it gives up and simply copies the individual.

    "Promotion" means to take a node n whose parent is m, and replacing the subtree rooted at m with the subtree rooted at n.

    A "Promotable" node means a node which is capable of promotion given the existing type constraints. In general to promote a node foo, foo must have a parent node, and must be type-compatible with the child slot that its parent fills.

    Typical Number of Individuals Produced Per produce(...) call
    ...as many as the source produces

    Number of Sources
    1

    Parameters

    base.tries
    int >= 1
    (number of times to try finding valid pairs of nodes)
    base.tree.0
    0 < int < (num trees in individuals), if exists
    (tree chosen for mutation; if parameter doesn't exist, tree is picked at random)

    Default Base
    gp.breed.mutate-promote

    See Also:
    Serialized Form
    • Constructor Detail

      • MutatePromotePipeline

        public MutatePromotePipeline()
    • Method Detail

      • defaultBase

        public Parameter defaultBase()
        Description copied from interface: Prototype
        Returns the default base for this prototype. This should generally be implemented by building off of the static base() method on the DefaultsForm object for the prototype's package. This should be callable during setup(...).
      • numSources

        public int numSources()
        Description copied from class: BreedingPipeline
        Returns the number of sources to this pipeline. Called during BreedingPipeline's setup. Be sure to return a value > 0, or DYNAMIC_SOURCES which indicates that setup should check the parameter file for the parameter "num-sources" to make its determination.
        Specified by:
        numSources in class BreedingPipeline
      • setup

        public void setup(EvolutionState state,
                          Parameter base)
        Description copied from class: BreedingSource
        Sets up the BreedingPipeline. You can use state.output.error here because the top-level caller promises to call exitIfErrors() after calling setup. Note that probability might get modified again by an external source if it doesn't normalize right.

        The most common modification is to normalize it with some other set of probabilities, then set all of them up in increasing summation; this allows the use of the fast static BreedingSource-picking utility method, BreedingSource.pickRandom(...). In order to use this method, for example, if four breeding source probabilities are {0.3, 0.2, 0.1, 0.4}, then they should get normalized and summed by the outside owners as: {0.3, 0.5, 0.6, 1.0}.

        Specified by:
        setup in interface Prototype
        Specified by:
        setup in interface Setup
        Overrides:
        setup in class BreedingPipeline
        See Also:
        Prototype.setup(EvolutionState,Parameter)
      • produce

        public int produce(int min,
                           int max,
                           int start,
                           int subpopulation,
                           Individual[] inds,
                           EvolutionState state,
                           int thread)
        Description copied from class: BreedingSource
        Produces n individuals from the given subpopulation and puts them into inds[start...start+n-1], where n = Min(Max(q,min),max), where q is the "typical" number of individuals the BreedingSource produces in one shot, and returns n. max must be >= min, and min must be >= 1. For example, crossover might typically produce two individuals, tournament selection might typically produce a single individual, etc.
        Specified by:
        produce in class BreedingSource

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